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dc.contributor.authorKrebs, W
dc.contributor.authorSchmidt, SV
dc.contributor.authorGoren, A
dc.contributor.authorDe Nardo, D
dc.contributor.authorLabzin, L
dc.contributor.authorBovier, A
dc.contributor.authorUlas, T
dc.contributor.authorTheis, H
dc.contributor.authorKraut, M
dc.contributor.authorLatz, E
dc.contributor.authorBeyer, M
dc.contributor.authorSchultze, JL
dc.date.accessioned2020-12-18T04:32:48Z
dc.date.available2020-12-18T04:32:48Z
dc.date.issued2014-12-01
dc.identifierpii: gku1078
dc.identifier.citationKrebs, W., Schmidt, S. V., Goren, A., De Nardo, D., Labzin, L., Bovier, A., Ulas, T., Theis, H., Kraut, M., Latz, E., Beyer, M. & Schultze, J. L. (2014). Optimization of transcription factor binding map accuracy utilizing knockout-mouse models. NUCLEIC ACIDS RESEARCH, 42 (21), pp.13051-13060. https://doi.org/10.1093/nar/gku1078.
dc.identifier.issn0305-1048
dc.identifier.urihttp://hdl.handle.net/11343/256242
dc.description.abstractGenome-wide assessment of protein-DNA interaction by chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) is a key technology for studying transcription factor (TF) localization and regulation of gene expression. Signal-to-noise-ratio and signal specificity in ChIP-seq studies depend on many variables, including antibody affinity and specificity. Thus far, efforts to improve antibody reagents for ChIP-seq experiments have focused mainly on generating higher quality antibodies. Here we introduce KOIN (knockout implemented normalization) as a novel strategy to increase signal specificity and reduce noise by using TF knockout mice as a critical control for ChIP-seq data experiments. Additionally, KOIN can identify 'hyper ChIPable regions' as another source of false-positive signals. As the use of the KOIN algorithm reduces false-positive results and thereby prevents misinterpretation of ChIP-seq data, it should be considered as the gold standard for future ChIP-seq analyses, particularly when developing ChIP-assays with novel antibody reagents.
dc.languageEnglish
dc.publisherOXFORD UNIV PRESS
dc.titleOptimization of transcription factor binding map accuracy utilizing knockout-mouse models
dc.typeJournal Article
dc.identifier.doi10.1093/nar/gku1078
melbourne.affiliation.departmentMedical Biology (W.E.H.I.)
melbourne.source.titleNucleic Acids Research
melbourne.source.volume42
melbourne.source.issue21
melbourne.source.pages13051-13060
dc.rights.licenseCC BY
melbourne.elementsid1317867
melbourne.contributor.authorde Nardo, Dominic
dc.identifier.eissn1362-4962
melbourne.accessrightsOpen Access


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